Deeploy

About Deeploy

Deeploy is an enterprise-grade AI governance platform designed to bring order, compliance, and trust to organizations scaling artificial intelligence. It acts as the central nervous system for an organization's entire AI portfolio, providing the critical oversight infrastructure that is often missing. The platform is built for Chief Technology Officers, Heads of AI, Risk & Compliance Officers, and engineering teams who are deploying AI across various models, vendors, and embedded systems. Its core value proposition is enabling businesses to innovate with AI faster while systematically managing the associated risks. By offering a unified interface for discovery, control, monitoring, and documentation, Deeploy transforms a fragmented "jungle of AI systems" into a governed, auditable, and compliant ecosystem. It directly addresses stringent regulatory demands like the EU AI Act, providing guided workflows and automated evidence collection to turn compliance from a burdensome cost center into an integrated, efficient process. Ultimately, Deeploy empowers organizations to maintain complete control and transparency over their AI initiatives, ensuring they can scale with confidence and build trustworthy AI systems.

Features of Deeploy

AI Discovery and Onboarding

This feature provides complete visibility across an organization's AI landscape. It allows teams to discover, onboard, and manage every AI system from a single, centralized interface. Deeploy connects to any existing MLOps or GenAI platform, eliminating blind spots without requiring painful migration projects. This creates a unified AI inventory and documentation hub, establishing the foundational layer for all subsequent governance and oversight activities, ensuring no AI initiative operates in the shadows.

Control Frameworks

Deeploy simplifies regulatory navigation with structured, guided workflows. Organizations can choose from default, pre-built control frameworks based on major standards like ISO 42001 and the NIST AI RMF, or build custom frameworks tailored to internal policies. The platform facilitates rapid AI system risk classification in minutes and establishes clear accountability through formalized approval processes. This turns complex compliance requirements into a straightforward, manageable operational routine.

Control Implementation

This feature translates high-level governance frameworks into enforceable, engineer-friendly controls. It provides development teams with clear, actionable requirements specific to each AI system's risk profile. Deeploy accelerates compliance by up to 90% through the use of templates and, crucially, the automated collection of evidence. It even employs AI-powered assessments to handle repetitive verification work, ensuring governance is practical and followed by engineering teams rather than being a theoretical hurdle.

Real-Time Monitoring

Deeploy offers proactive surveillance to prevent AI incidents before they impact users or create compliance breaches. It monitors AI performance and behavior in real-time, sending instant alerts for critical issues like model drift, performance degradation, or output anomalies. For generative AI applications, it adds tracing and guardrails to protect LLM outputs. This continuous oversight allows teams to identify and remediate errors before they escalate, ensuring AI systems operate reliably and as intended.

Use Cases of Deeploy

Achieving EU AI Act Compliance

Organizations operating in or selling to the European market use Deeploy as a dedicated compliance engine for the EU AI Act. The platform's guided workflows help classify AI systems by risk level, implement necessary controls, and automatically generate the required documentation and audit trails. This structured approach demystifies the regulation, turning a complex legal requirement into a streamlined operational process managed from a single pane of glass.

Centralizing Oversight for Fragmented AI Portfolios

Large enterprises with AI models scattered across different teams, cloud providers, and third-party vendors deploy Deeploy to gain a unified view. The discovery and onboarding feature creates a central registry, ending the chaos of undocumented systems. This centralization allows leadership to maintain oversight, allocate resources effectively, and ensure consistent governance standards are applied to every AI application, regardless of where it was built or hosted.

Enabling Safe AI in Regulated Industries

Companies in highly regulated sectors like healthcare, finance, and insurance leverage Deeploy to build trust and ensure safety. Features like real-time monitoring, explainability, and human feedback loops are critical. For instance, a mental healthcare platform can use Deeploy to monitor AI-assisted tools, provide clinicians with explanations for AI suggestions, and incorporate expert feedback to improve system safety and efficacy responsibly.

Accelerating MLOps with Governance-by-Design

AI and data science teams use Deeploy to integrate governance directly into their MLOps lifecycle. By onboarding models into Deeploy, engineers get clear compliance requirements from the start and benefit from automated evidence collection. This shifts governance left in the development process, preventing last-minute compliance scrambles and reducing the time from model development to governed, compliant deployment from weeks down to hours.

Frequently Asked Questions

How does Deeploy handle AI systems from different vendors and platforms?

Deeploy is designed as a unifying governance layer that sits on top of your existing AI stack. It offers flexible onboarding and connectors to integrate with a wide variety of MLOps platforms (like MLflow, Sagemaker) and GenAI vendors. This means you can discover, monitor, and govern AI systems regardless of where they are built or hosted, creating a centralized oversight point without forcing a migration to a single new platform.

Can Deeploy support custom internal policies beyond major regulations like the AI Act?

Absolutely. While Deeploy provides pre-built templates for major frameworks like ISO 42001 and the NIST AI RMF, it is fully customizable. Organizations can build their own control frameworks tailored to specific internal risk management policies, industry standards, or ethical AI principles. This flexibility ensures the platform can adapt to your unique governance needs and evolve as your policies mature.

What kind of "explainability" does Deeploy provide?

Deeploy provides built-in explainability features that help users understand how AI models arrive at their predictions or outputs. This is crucial for debugging, building trust, and meeting regulatory requirements for transparency. The explanations are presented in an accessible way, useful for both technical experts and non-technical stakeholders, allowing them to understand model behavior and outcomes more easily.

How does the real-time monitoring actually work to prevent incidents?

Deeploy's monitoring continuously tracks key performance indicators, data drift, and system behavior for all onboarded AI models. It uses configurable thresholds and anomaly detection to identify issues like accuracy drops or unexpected output patterns. When a potential problem is detected, the system triggers instant alerts to relevant teams via their preferred channels (e.g., Slack, email), enabling proactive intervention before the issue affects end-users or leads to a compliance violation.